Detecting Compromised IoT Devices Using Autoencoders with Sequential Hypothesis Testing

arXiv:2404.13690v1 Announce Type: new
Abstract: IoT devices fundamentally lack built-in security mechanisms to protect themselves from security attacks. Existing works on improving IoT security mostly focus on detecting anomalous behaviors of IoT devices. However, these existing anomaly detection schemes may trigger an overwhelmingly large number of false alerts, rendering them unusable in detecting compromised IoT devices. In this paper we develop an effective and efficient framework, named CUMAD, to detect compromised IoT devices. Instead of directly relying on individual anomalous …

alerts anomaly detection arxiv attacks autoencoders compromised cs.cr cs.lg detection devices focus iot iot devices iot security large may protect security security attacks testing trigger